


'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


UpperCAmelCase_						:  int				  =						{
    'configuration_mvp': ['MVP_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MvpConfig', 'MvpOnnxConfig'],
    'tokenization_mvp': ['MvpTokenizer'],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_						:  Tuple				  =						['MvpTokenizerFast']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_						:  Any				  =						[
				    'MVP_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'MvpForCausalLM',
				    'MvpForConditionalGeneration',
				    'MvpForQuestionAnswering',
				    'MvpForSequenceClassification',
				    'MvpModel',
				    'MvpPreTrainedModel',
				]

if TYPE_CHECKING:
				from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
				from .tokenization_mvp import MvpTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_mvp_fast import MvpTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_mvp import (
								    MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
								    MvpForCausalLM,
								    MvpForConditionalGeneration,
								    MvpForQuestionAnswering,
								    MvpForSequenceClassification,
								    MvpModel,
								    MvpPreTrainedModel,
								)

else:
				import sys

				UpperCAmelCase_						:  Any				  =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








'''simple docstring'''


import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
				from PIL import Image

				from transformers import CLIPSegProcessor, ViTImageProcessor





@require_vision
class        lowercase__    (		unittest.TestCase   ):





							'''simple docstring'''


							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			List[str]							= tempfile.mkdtemp()

											# fmt: off
											_SCREAMING_SNAKE_CASE					:			Any							= ["""l""", """o""", """w""", """e""", """r""", """s""", """t""", """i""", """d""", """n""", """lo""", """l</w>""", """w</w>""", """r</w>""", """t</w>""", """low</w>""", """er</w>""", """lowest</w>""", """newer</w>""", """wider""", """<unk>""", """<|startoftext|>""", """<|endoftext|>"""]
											# fmt: on
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= dict(zip(__snake_case       ,   range(len(__snake_case    )    )    )    )
											_SCREAMING_SNAKE_CASE					:			str							= ["""#version: 0.2""", """l o""", """lo w</w>""", """e r</w>""", """"""]
											_SCREAMING_SNAKE_CASE					:			Any							= {"""unk_token""": """<unk>"""}

											_SCREAMING_SNAKE_CASE					:			Optional[int]							= os.path.join(self.tmpdirname       ,   VOCAB_FILES_NAMES["""vocab_file"""]    )
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= os.path.join(self.tmpdirname       ,   VOCAB_FILES_NAMES["""merges_file"""]    )
											with open(self.vocab_file       ,   """w"""       ,   encoding="""utf-8"""    ) as fp:
															fp.write(json.dumps(__snake_case    ) + """\n"""    )
											with open(self.merges_file       ,   """w"""       ,   encoding="""utf-8"""    ) as fp:
															fp.write("""\n""".join(__snake_case    )    )

											_SCREAMING_SNAKE_CASE					:			Any							= {
											    """do_resize""": True,
											    """size""": 20,
											    """do_center_crop""": True,
											    """crop_size""": 18,
											    """do_normalize""": True,
											    """image_mean""": [0.48145466, 0.4578275, 0.40821073],
											    """image_std""": [0.26862954, 0.26130258, 0.27577711],
											}
											_SCREAMING_SNAKE_CASE					:			List[str]							= os.path.join(self.tmpdirname       ,   __snake_case    )
											with open(self.image_processor_file       ,   """w"""       ,   encoding="""utf-8"""    ) as fp:
															json.dump(__snake_case       ,   __snake_case    )






							def UpperCAmelCase_      (       self       ,   **__snake_case    ):
											return CLIPTokenizer.from_pretrained(self.tmpdirname       ,   **__snake_case    )






							def UpperCAmelCase_      (       self       ,   **__snake_case    ):
											return CLIPTokenizerFast.from_pretrained(self.tmpdirname       ,   **__snake_case    )






							def UpperCAmelCase_      (       self       ,   **__snake_case    ):
											return ViTImageProcessor.from_pretrained(self.tmpdirname       ,   **__snake_case    )






							def UpperCAmelCase_      (       self    ):
											shutil.rmtree(self.tmpdirname    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= [np.random.randint(255       ,   size=(3, 30, 400)       ,   dtype=np.uinta    )]

											_SCREAMING_SNAKE_CASE					:			List[str]							= [Image.fromarray(np.moveaxis(__snake_case       ,   0       ,   -1    )    ) for x in image_inputs]

											return image_inputs






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			List[str]							= self.get_tokenizer()
											_SCREAMING_SNAKE_CASE					:			int							= self.get_rust_tokenizer()
											_SCREAMING_SNAKE_CASE					:			Dict							= self.get_image_processor()

											_SCREAMING_SNAKE_CASE					:			str							= CLIPSegProcessor(tokenizer=__snake_case       ,   image_processor=__snake_case    )
											processor_slow.save_pretrained(self.tmpdirname    )
											_SCREAMING_SNAKE_CASE					:			List[str]							= CLIPSegProcessor.from_pretrained(self.tmpdirname       ,   use_fast=__snake_case    )

											_SCREAMING_SNAKE_CASE					:			Any							= CLIPSegProcessor(tokenizer=__snake_case       ,   image_processor=__snake_case    )
											processor_fast.save_pretrained(self.tmpdirname    )
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= CLIPSegProcessor.from_pretrained(self.tmpdirname    )

											self.assertEqual(processor_slow.tokenizer.get_vocab()       ,   tokenizer_slow.get_vocab()    )
											self.assertEqual(processor_fast.tokenizer.get_vocab()       ,   tokenizer_fast.get_vocab()    )
											self.assertEqual(tokenizer_slow.get_vocab()       ,   tokenizer_fast.get_vocab()    )
											self.assertIsInstance(processor_slow.tokenizer       ,   __snake_case    )
											self.assertIsInstance(processor_fast.tokenizer       ,   __snake_case    )

											self.assertEqual(processor_slow.image_processor.to_json_string()       ,   image_processor.to_json_string()    )
											self.assertEqual(processor_fast.image_processor.to_json_string()       ,   image_processor.to_json_string()    )
											self.assertIsInstance(processor_slow.image_processor       ,   __snake_case    )
											self.assertIsInstance(processor_fast.image_processor       ,   __snake_case    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			int							= CLIPSegProcessor(tokenizer=self.get_tokenizer()       ,   image_processor=self.get_image_processor()    )
											processor.save_pretrained(self.tmpdirname    )

											_SCREAMING_SNAKE_CASE					:			str							= self.get_tokenizer(bos_token="""(BOS)"""       ,   eos_token="""(EOS)"""    )
											_SCREAMING_SNAKE_CASE					:			List[str]							= self.get_image_processor(do_normalize=__snake_case       ,   padding_value=1.0    )

											_SCREAMING_SNAKE_CASE					:			Tuple							= CLIPSegProcessor.from_pretrained(
											    self.tmpdirname       ,   bos_token="""(BOS)"""       ,   eos_token="""(EOS)"""       ,   do_normalize=__snake_case       ,   padding_value=1.0    )

											self.assertEqual(processor.tokenizer.get_vocab()       ,   tokenizer_add_kwargs.get_vocab()    )
											self.assertIsInstance(processor.tokenizer       ,   __snake_case    )

											self.assertEqual(processor.image_processor.to_json_string()       ,   image_processor_add_kwargs.to_json_string()    )
											self.assertIsInstance(processor.image_processor       ,   __snake_case    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= self.get_image_processor()
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= self.get_tokenizer()

											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= CLIPSegProcessor(tokenizer=__snake_case       ,   image_processor=__snake_case    )

											_SCREAMING_SNAKE_CASE					:			List[Any]							= self.prepare_image_inputs()

											_SCREAMING_SNAKE_CASE					:			List[Any]							= image_processor(__snake_case       ,   return_tensors="""np"""    )
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= processor(images=__snake_case       ,   return_tensors="""np"""    )

											for key in input_feat_extract.keys():
															self.assertAlmostEqual(input_feat_extract[key].sum()       ,   input_processor[key].sum()       ,   delta=1e-2    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			List[str]							= self.get_image_processor()
											_SCREAMING_SNAKE_CASE					:			Dict							= self.get_tokenizer()

											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= CLIPSegProcessor(tokenizer=__snake_case       ,   image_processor=__snake_case    )

											_SCREAMING_SNAKE_CASE					:			str							= """lower newer"""

											_SCREAMING_SNAKE_CASE					:			Any							= processor(text=__snake_case    )

											_SCREAMING_SNAKE_CASE					:			Tuple							= tokenizer(__snake_case    )

											for key in encoded_tok.keys():
															self.assertListEqual(encoded_tok[key]       ,   encoded_processor[key]    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= self.get_image_processor()
											_SCREAMING_SNAKE_CASE					:			List[Any]							= self.get_tokenizer()

											_SCREAMING_SNAKE_CASE					:			Dict							= CLIPSegProcessor(tokenizer=__snake_case       ,   image_processor=__snake_case    )

											_SCREAMING_SNAKE_CASE					:			Any							= """lower newer"""
											_SCREAMING_SNAKE_CASE					:			List[Any]							= self.prepare_image_inputs()

											_SCREAMING_SNAKE_CASE					:			List[str]							= processor(text=__snake_case       ,   images=__snake_case    )

											self.assertListEqual(list(inputs.keys()    )       ,   ["""input_ids""", """attention_mask""", """pixel_values"""]    )

											# test if it raises when no input is passed
											with pytest.raises(__snake_case    ):
															processor()






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			Dict							= self.get_image_processor()
											_SCREAMING_SNAKE_CASE					:			Tuple							= self.get_tokenizer()

											_SCREAMING_SNAKE_CASE					:			List[Any]							= CLIPSegProcessor(tokenizer=__snake_case       ,   image_processor=__snake_case    )

											_SCREAMING_SNAKE_CASE					:			str							= self.prepare_image_inputs()
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= self.prepare_image_inputs()

											_SCREAMING_SNAKE_CASE					:			List[Any]							= processor(images=__snake_case       ,   visual_prompt=__snake_case    )

											self.assertListEqual(list(inputs.keys()    )       ,   ["""pixel_values""", """conditional_pixel_values"""]    )

											# test if it raises when no input is passed
											with pytest.raises(__snake_case    ):
															processor()






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= self.get_image_processor()
											_SCREAMING_SNAKE_CASE					:			Dict							= self.get_tokenizer()

											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= CLIPSegProcessor(tokenizer=__snake_case       ,   image_processor=__snake_case    )

											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

											_SCREAMING_SNAKE_CASE					:			int							= processor.batch_decode(__snake_case    )
											_SCREAMING_SNAKE_CASE					:			int							= tokenizer.batch_decode(__snake_case    )

											self.assertListEqual(__snake_case       ,   __snake_case    )




